Abstract

To obtain secure and accurate authentication system using most accepted biometrics Hand geometry in multimodal approach. Implement multi modal person authentication system using single input image with efficient features. In this proposed method Hand geometry and selected window size palm print features computed from same image is used for authentication. Integrating the features increases robustness of the system. Discrete Wavelet Transform (DWT) is used for feature extraction and Support Vector Machine (SVM) is proposed for classification. The final decision is made by fusion at matching score level. Experiments are carried out on the publicly available GPDS Hand Database. The achieved experimental results GAR=99. 47%, FAR=0% showed the effectiveness of system considered for high security applications.

References

• A. K. Jain, A. , Ross, & S. Prabhakar, "An Introduction to biometric recognition," IEEE Transactions on Circuits System and Video Technology , vol. 14 (1), pp. 4-20, 2004.
• Ashish Mishra, 'Multimoda Biometrics it is; Need for Future systems', International Journal of Computer Applications, vol 3-No 4,June 2010,pp 28-33.
• Hand-based Biometrics, Biometric Technology Today, vol. 11, no. 7, 2003, pp. 9-11.
• R. M. Rao and A. S. Bopardikar, "Wavelet Transforms-Introduction to theory and Applications", Addison Wesley Longman,1998.
• C. J. C. Burges, "A Tutorial on support vector machines for pattern Recognition", Data Mining and Knowledge discovery,vol 2:121-167,1998.
• M. Pontil, A. Verri, "Support Vector Machines for 3-d Object Recognition", IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 35-39, 1998.
• A. K. Jain, A. Ross and S. Pankanti, uA Prototype Hand Geometry-based Verification System", 2nd Int. Conference on Audio- and Video-based Pernal Authentication (AVBPA), Washington, pp. 166-171, March 1999.
• R. Sanchez-Reillo, C. Sanchez-Avila and A. Gonzalez- Marcos, "Biometric Identification Through Hand Geometry Measurements", IEEE Transactions onPaffem Analysis Machine Intelligence, Vol. 22, No. 10, pp. 1168-1171, 2000.
• A. K. Jain and N. Duta, "Deformable Matching of Hand Shapes for Verification',Proceedings of IEEE International Conference on Image Processing, Kobe, October 1999.
• A. Wong and P. Shi, "Peg-free hand geometry recognition using hierarchical geometry and shape matching," in Proc. IAPR Workshop on Machine Vision Applications, Nara, Japan, Dec. 2002, pp. 281–284 [Online]. Available: http://www. ee. ust. hk/~eeship/Papers/MVA02. pdf.
• Y. Bulatov, S. Jambawalikar, P. Kumar, and S. Sethia, "Hand recognition using geometric classifiers," in Proc. 1st Int. Conf. Biometric Authentication, Hong Kong, China, Jul. 2004, pp. 753–759.
• G. Boreki and A. Zimmer, "Hand geometry: A new approach for feature extraction," in Proc. 4th IEEE Workshop on Automatic Identification Advanced Technologies, Oct. 2005, pp. 149–154.
• D. Zhang, W. K. Kong, J. You, and M. Wong, "Online Palm Print Identification," IEEE Trans Pattern Analysis and Machine Intelligence, vol. 25, no. 2, pp. 1041-1050, Feb. 2003.
• Hafiz Imtiaz and Shaikh Anowarul Fattah, "A DCT-based Feature Extraction Algorithm for Palm-print Recognition", IEEE International Conference on Communication Control and Computing Technologies, October 2010, pp 657-660.
• Chin-Chuan Han and Hsu-Liang Cheng, "Personal Authentication Using Palm Print Features", 5th Asian Conference on Computer Vision, January 2002, pp 1-6.
• Jane You and Wenxin Li, "Hierarchical palm print identification via multiple feature extraction", Journal of Pattern Recognition, April 2002, pp 847-859.
• C. C. Han, H. -L. Cheng, C. -L. Lin and K. -C. Fan, "Personal authentication using palm print features," Pattern Recognition, vol. 36, pp. 371-381, 2003.
• Kumar, A. , Wong, D. , Shen, H. and Jain, A. , "Personal Verification Using Palm print and Hand Geometry Biometric", in Proc. 4th International Conference on Audio- and Video-based Biometric Person Authentication, Guildford, U. K. , June 2003, pp. 668-678.
• S. Ribaric, 1. Fratric, "A Biometric Identification System Based on EigenPalm and EigenFinger Features", in IEEE Transactions on Paffem Analysis and Machine Intelligence", vol. 27, no. 11, pp. 1698-1709, November 2005.
• A. Kumar, D. Zhang, "Personal Recognition Using Hand Shape and Texture", in IEEE Transaction on image Processing, vol. 15, no. 8, pp. 2454-2461, 2006.
• M. Ong, T. Connie, A. Jin, and D. Ling, "A single-sensor hand geometry and plamprint verification system," in Proc. ACM SIGMM Workshop Biometrics Methods and Applications, Berkley, CA, 2003, pp. 100–106.
• T Sanches, J Antunes, and P L Correia, "A Single Sensor Hand Biometric Multimodal System," in 15th European Signal Processing Conference (EUSIPCO), Poznan, Poland, 2007, pp. 30-34
• S. Sumathi and R. Ranihemamalini, "Multi-biometric Authentication using DWT and Score Level Fusion", European Journal of Scientific Research, Vol 80, No 2 pp 213-223,2012.
• J. Kittler, M. Hatef, R. Duin, and J. Matas, "On combining classifiers," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 20, no. 3, pp. 226–239, Mar. 1998.
• S. H. Lin ,S. Y. Kung and L. J. Lin,"Face Recognition / Detection by Probalistic Decision –based Neural Network",IEEE Trans. Neural Networks,vol 8,no 1,pp 114-132,Jan. 1997.
• Miguel A. Ferrer1, Joan Fàbregas2, Marcos Faundez2, Jesús B. Alonso1, Carlos Travies "Hand Geometry Identification System Performance" IEEE conference2009,pp167-171. [27 a] S. Sumathi and R. Ranihemamalini, "Personal Identification Using Palm Print Features With an Efficient Method of DWT" Springer,Part II, CCIS 270,2012,pp337-343. [27 b] S. Sumathi and R. Ranihemamalini, "An Efficient Method for Person Identification Using Wavelet Transform with Palm Print Features", National Jou
• X. -Y. Jing, Y. -F. Yao, D. Zhang, J. -Y. Yang, and M. Li, "Face and palmprint pixel level fusion and kernel dcv-rbf classifier for small sample biometric recognition," Pattern Recognition, vol. 40, no. 11, pp. 3209–3224, 2007.
• L. Hong, A. Jain, and S. Pankanti, "Can multibiometrics improve performance," in Proceedings of IEEE Workshop on Automatic Identification Advanced Technologies, pp. 59–64, 1999.
• L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their applications to handwriting recognition," IEEE Transactions on Systems, Man and Cybernetics, vol. 22, no. 3, pp. 418–435, 1992.
• K. Nandakumar, Y. Chen, S. C. Dass, A. K. Jain, Likelihood ratio-based biometric score fusion, IEEE Transactions on Pattern Analysis and Machine Intelligence 30 (2) (2008) 342–347.
• C. Bergamini, et al. , Combining different biometric traits with one-class classification, Signal Processing 89 (11) (2009) pp 2117–2127.
• M. He, et al. , Performance evaluation of score level fusion in multimodal biometric systems Pattern Recognition (2009), doi:10. 1016/j. patcog. 2009. 11. 018
• GPDS hand database, http://www. gpds. ulpgc. es/download/.